Genetic and clinical factors associated with the metabolism of valproic acid in post-neurosurgery patients

Valproic acid (VPA) is commonly used to treat epilepsy and bipolar disorder, requiring therapeutic concentrations of 50–100 mg/L to balance efficacy and safety. Despite known clinical and genetic factors influencing VPA metabolism, integrated predictive models are limited. This study analyzed VPA concentrations in 497 samples from 275 Chinese participants, examining 23 clinical variables and 24 genetic SNPs. Participants were grouped by SNP profiles, with one cluster showing significantly elevated VPA levels. Key factors influencing VPA concentrations included genetic variants (e.g., rs12233719, rs12769205, CYP2C19 SNPs), dosage interval, solvent volume, BMI, and propacetamol co-administration. Network analysis highlighted the independence of genetic and clinical variables in influencing VPA concentrations. A regression model with the random forest algorithm demonstrated superior performance, with dosage interval, BMI, and genetic factors among the top predictors. A classification model using a parallel random forest algorithm achieved a median accuracy of 73 % in distinguishing VPA concentrations below the therapeutic threshold. Functional analyses linked associated SNPs to CYP-mediated omega-oxidation. This study highlights the interplay of genetic and clinical factors in VPA metabolism, advancing personalized dosing strategies to improve outcomes and minimize side effects.